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<div class="title">object_recognition.h</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="preprocessor">#ifndef OBJECT_RECOGNITION_H_</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="preprocessor">#define OBJECT_RECOGNITION_H_</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160; </div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="preprocessor">#include &quot;typedefs.h&quot;</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="preprocessor">#include &quot;load_clouds.h&quot;</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#include &quot;solution/filters.h&quot;</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">#include &quot;solution/segmentation.h&quot;</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &quot;solution/feature_estimation.h&quot;</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="preprocessor">#include &quot;solution/registration.h&quot;</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160; </div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &lt;pcl/io/pcd_io.h&gt;</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &lt;pcl/kdtree/kdtree_flann.h&gt;</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160; </div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160; </div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="keyword">struct </span><a class="code" href="struct_object_recognition_parameters.html">ObjectRecognitionParameters</a></div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;{</div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;  <span class="comment">// Filter parameters</span></div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;  <span class="keywordtype">float</span> min_depth;</div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;  <span class="keywordtype">float</span> max_depth;</div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;  <span class="keywordtype">float</span> downsample_leaf_size;</div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;  <span class="keywordtype">float</span> outlier_rejection_radius;</div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;  <span class="keywordtype">int</span> outlier_rejection_min_neighbors;</div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160; </div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;  <span class="comment">// Segmentation parameters</span></div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;  <span class="keywordtype">float</span> plane_inlier_distance_threshold;</div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;  <span class="keywordtype">int</span> max_ransac_iterations;</div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;  <span class="keywordtype">float</span> cluster_tolerance;</div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;  <span class="keywordtype">int</span> min_cluster_size;</div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;  <span class="keywordtype">int</span> max_cluster_size;</div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160; </div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;  <span class="comment">// Feature estimation parameters</span></div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;  <span class="keywordtype">float</span> surface_normal_radius;</div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;  <span class="keywordtype">float</span> keypoints_min_scale;</div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;  <span class="keywordtype">float</span> keypoints_nr_octaves;</div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;  <span class="keywordtype">float</span> keypoints_nr_scales_per_octave;</div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;  <span class="keywordtype">float</span> keypoints_min_contrast;</div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;  <span class="keywordtype">float</span> local_descriptor_radius;</div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160; </div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;  <span class="comment">// Registration parameters</span></div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;  <span class="keywordtype">float</span> initial_alignment_min_sample_distance;</div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;  <span class="keywordtype">float</span> initial_alignment_max_correspondence_distance;</div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;  <span class="keywordtype">int</span> initial_alignment_nr_iterations;</div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;  <span class="keywordtype">float</span> icp_max_correspondence_distance;</div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;  <span class="keywordtype">float</span> icp_outlier_rejection_threshold;</div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;  <span class="keywordtype">float</span> icp_transformation_epsilon;</div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;  <span class="keywordtype">int</span> icp_max_iterations;</div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;};</div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160; </div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;<span class="keyword">struct </span><a class="code" href="struct_object_model.html">ObjectModel</a></div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;{</div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;  PointCloudPtr points;</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;  PointCloudPtr keypoints;</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;  LocalDescriptorsPtr local_descriptors;</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;  GlobalDescriptorsPtr global_descriptor;</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;};</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160; </div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;<span class="keyword">class </span><a class="code" href="class_object_recognition.html">ObjectRecognition</a></div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;{</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;  <span class="keyword">public</span>:</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <a class="code" href="class_object_recognition.html">ObjectRecognition</a> (<span class="keyword">const</span> <a class="code" href="struct_object_recognition_parameters.html">ObjectRecognitionParameters</a> &amp; params) : params_ (params)</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    {}</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160; </div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    <span class="keywordtype">void</span> </div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    populateDatabase (<span class="keyword">const</span> std::vector&lt;std::string&gt; &amp; filenames)</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    {</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;      <span class="keywordtype">size_t</span> n = filenames.size ();</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;      models_.resize (n);</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;      descriptors_ = GlobalDescriptorsPtr (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">GlobalDescriptors</a>);</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; n; ++i)</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;      {</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;        <span class="keyword">const</span> std::string &amp; filename = filenames[i];</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;        <span class="keywordflow">if</span> (filename.compare (filename.size ()-4, 4, <span class="stringliteral">&quot;.pcd&quot;</span>) == 0)</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        {</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;          <span class="comment">// If filename ends pcd extension, load the points and process them</span></div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;          PointCloudPtr raw_input (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">PointCloud</a>);</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;          pcl::io::loadPCDFile (filenames[i], *raw_input);</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;          </div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;          constructObjectModel (raw_input, models_[i]);</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;        }</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;        <span class="keywordflow">else</span></div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;        {</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;          <span class="comment">// If the filename has no extension, load the pre-computed models</span></div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;          models_[i].points = loadPointCloud&lt;PointT&gt; (filename, <span class="stringliteral">&quot;_points.pcd&quot;</span>);</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;          models_[i].keypoints = loadPointCloud&lt;PointT&gt; (filename, <span class="stringliteral">&quot;_keypoints.pcd&quot;</span>);</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;          models_[i].local_descriptors = loadPointCloud&lt;LocalDescriptorT&gt; (filename, <span class="stringliteral">&quot;_localdesc.pcd&quot;</span>);</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;          models_[i].global_descriptor = loadPointCloud&lt;GlobalDescriptorT&gt; (filename, <span class="stringliteral">&quot;_globaldesc.pcd&quot;</span>);       </div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;        }</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;        *descriptors_ += *(models_[i].global_descriptor);</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;      }</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;      kdtree_ = pcl::KdTreeFLANN&lt;GlobalDescriptorT&gt;::Ptr (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_kd_tree_f_l_a_n_n.html">pcl::KdTreeFLANN&lt;GlobalDescriptorT&gt;</a>);</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;      kdtree_-&gt;setInputCloud (descriptors_);</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    } </div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160; </div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;    <span class="keyword">const</span> <a class="code" href="struct_object_model.html">ObjectModel</a> &amp; </div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;    recognizeObject (<span class="keyword">const</span> PointCloudPtr &amp; query_cloud)</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    {</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;      <a class="code" href="struct_object_model.html">ObjectModel</a> query_object;</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;      constructObjectModel (query_cloud, query_object);</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;      <span class="keyword">const</span> <a class="code" href="structpcl_1_1_v_f_h_signature308.html">GlobalDescriptorT</a> &amp; query_descriptor = query_object.global_descriptor-&gt;points[0];</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;      </div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;      std::vector&lt;int&gt; nn_index (1);</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;      std::vector&lt;float&gt; nn_sqr_distance (1);</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;      kdtree_-&gt;nearestKSearch (query_descriptor, 1, nn_index, nn_sqr_distance);</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;      <span class="keyword">const</span> <span class="keywordtype">int</span> &amp; best_match = nn_index[0];</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160; </div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;      <span class="keywordflow">return</span> (models_[best_match]);</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;    }</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160; </div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    PointCloudPtr</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;    recognizeAndAlignPoints (<span class="keyword">const</span> PointCloudPtr &amp; query_cloud)</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;    {</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;      <a class="code" href="struct_object_model.html">ObjectModel</a> query_object;</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;      constructObjectModel (query_cloud, query_object);</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;      <span class="keyword">const</span> <a class="code" href="structpcl_1_1_v_f_h_signature308.html">GlobalDescriptorT</a> &amp; query_descriptor = query_object.global_descriptor-&gt;points[0];</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;      </div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;      std::vector&lt;int&gt; nn_index (1);</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;      std::vector&lt;float&gt; nn_sqr_distance (1);</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;      kdtree_-&gt;nearestKSearch (query_descriptor, 1, nn_index, nn_sqr_distance);</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;      <span class="keyword">const</span> <span class="keywordtype">int</span> &amp; best_match = nn_index[0];</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160; </div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;      PointCloudPtr output = alignModelPoints (models_[best_match], query_object, params_);</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;      <span class="keywordflow">return</span> (output);</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    }</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160; </div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    <span class="comment">/* Construct an object model by filtering, segmenting, and estimating feature descriptors */</span></div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;    <span class="keywordtype">void</span></div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    constructObjectModel (<span class="keyword">const</span> PointCloudPtr &amp; points, <a class="code" href="struct_object_model.html">ObjectModel</a> &amp; output)<span class="keyword"> const</span></div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;<span class="keyword">    </span>{</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;      output.points = applyFiltersAndSegment (points, params_);</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160; </div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;      SurfaceNormalsPtr normals;</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;      estimateFeatures (output.points, params_, normals, output.keypoints, </div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;                        output.local_descriptors, output.global_descriptor);</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    }</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160; </div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;  <span class="keyword">protected</span>: </div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;    <span class="comment">/* Apply a series of filters (threshold depth, downsample, and remove outliers) */</span></div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    PointCloudPtr</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    applyFiltersAndSegment (<span class="keyword">const</span> PointCloudPtr &amp; input, <span class="keyword">const</span> <a class="code" href="struct_object_recognition_parameters.html">ObjectRecognitionParameters</a> &amp; params)<span class="keyword"> const</span></div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;<span class="keyword">    </span>{</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;      PointCloudPtr cloud;</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;      cloud = thresholdDepth (input, params.min_depth, params.max_depth);</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;      cloud = downsample (cloud, params.downsample_leaf_size);</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;      cloud = removeOutliers (cloud, params.outlier_rejection_radius, params.outlier_rejection_min_neighbors);</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160; </div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;      cloud = findAndSubtractPlane (cloud, params.plane_inlier_distance_threshold, params.max_ransac_iterations);</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;      std::vector&lt;pcl::PointIndices&gt; cluster_indices;</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;      clusterObjects (cloud, params.cluster_tolerance, params.min_cluster_size, </div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;                      params.max_cluster_size, cluster_indices);</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160; </div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;      PointCloudPtr largest_cluster (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">PointCloud</a>);</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;      <a class="code" href="group__common.html#gaa65b1c8d782e7b776ae682679d2d948f">pcl::copyPointCloud</a> (*cloud, cluster_indices[0], *largest_cluster);</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160; </div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;      <span class="keywordflow">return</span> (largest_cluster);</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    }</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160; </div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    <span class="comment">/* Estimate surface normals, keypoints, and local/global feature descriptors */</span></div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;    <span class="keywordtype">void</span></div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;    estimateFeatures (<span class="keyword">const</span> PointCloudPtr &amp; points, <span class="keyword">const</span> <a class="code" href="struct_object_recognition_parameters.html">ObjectRecognitionParameters</a> &amp; params,</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;                      SurfaceNormalsPtr &amp; normals_out, PointCloudPtr &amp; keypoints_out, </div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;                      LocalDescriptorsPtr &amp; local_descriptors_out, GlobalDescriptorsPtr &amp; global_descriptor_out)<span class="keyword"> const</span></div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;<span class="keyword">    </span>{</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;      normals_out = estimateSurfaceNormals (points, params.surface_normal_radius);</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;      </div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;      keypoints_out = detectKeypoints (points, normals_out, params.keypoints_min_scale, params.keypoints_nr_octaves,</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;                                       params.keypoints_nr_scales_per_octave, params.keypoints_min_contrast);</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;      </div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;      local_descriptors_out = computeLocalDescriptors (points, normals_out, keypoints_out, </div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;                                                       params.local_descriptor_radius);</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;      </div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;      global_descriptor_out = computeGlobalDescriptor (points, normals_out);</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;    }</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160; </div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;    <span class="comment">/* Align the points in the source model to the points in the target model */</span></div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;    PointCloudPtr</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;    alignModelPoints (<span class="keyword">const</span> <a class="code" href="struct_object_model.html">ObjectModel</a> &amp; source, <span class="keyword">const</span> <a class="code" href="struct_object_model.html">ObjectModel</a> &amp; target, </div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;                      <span class="keyword">const</span> <a class="code" href="struct_object_recognition_parameters.html">ObjectRecognitionParameters</a> &amp; params)<span class="keyword"> const</span></div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;<span class="keyword">    </span>{</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;      Eigen::Matrix4f tform; </div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;      tform = computeInitialAlignment (source.keypoints, source.local_descriptors,</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;                                       target.keypoints, target.local_descriptors,</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;                                       params.initial_alignment_min_sample_distance,</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;                                       params.initial_alignment_max_correspondence_distance, </div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;                                       params.initial_alignment_nr_iterations);</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160; </div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;      tform = refineAlignment (source.points, target.points, tform, </div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;                               params.icp_max_correspondence_distance, params.icp_outlier_rejection_threshold, </div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;                               params.icp_transformation_epsilon, params.icp_max_iterations);</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160; </div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;      PointCloudPtr output (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">PointCloud</a>);</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;      <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a> (*(source.points), *output, tform);</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160; </div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;      <span class="keywordflow">return</span> (output);</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;    }  </div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160; </div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;    <a class="code" href="struct_object_recognition_parameters.html">ObjectRecognitionParameters</a> params_;</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;    std::vector&lt;ObjectModel&gt; models_;</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;    GlobalDescriptorsPtr descriptors_;</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    pcl::KdTreeFLANN&lt;GlobalDescriptorT&gt;::Ptr kdtree_;</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;};</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160; </div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="ttc" id="aclass_object_recognition_html"><div class="ttname"><a href="class_object_recognition.html">ObjectRecognition</a></div><div class="ttdef"><b>Definition:</b> object_recognition.h:58</div></div>
<div class="ttc" id="aclasspcl_1_1_kd_tree_f_l_a_n_n_html"><div class="ttname"><a href="classpcl_1_1_kd_tree_f_l_a_n_n.html">pcl::KdTreeFLANN</a></div><div class="ttdoc">KdTreeFLANN is a generic type of 3D spatial locator using kD-tree structures. The class is making use...</div><div class="ttdef"><b>Definition:</b> kdtree_flann.h:70</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html"><div class="ttname"><a href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt; GlobalDescriptorT &gt;</a></div></div>
<div class="ttc" id="agroup__common_html_ga52d532f7f2b4d7bba78d13701d3a33d8"><div class="ttname"><a href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a></div><div class="ttdeci">void transformPointCloud(const pcl::PointCloud&lt; PointT &gt; &amp;cloud_in, pcl::PointCloud&lt; PointT &gt; &amp;cloud_out, const Eigen::Transform&lt; Scalar, 3, Eigen::Affine &gt; &amp;transform, bool copy_all_fields=true)</div><div class="ttdoc">Apply an affine transform defined by an Eigen Transform</div><div class="ttdef"><b>Definition:</b> transforms.hpp:42</div></div>
<div class="ttc" id="agroup__common_html_gaa65b1c8d782e7b776ae682679d2d948f"><div class="ttname"><a href="group__common.html#gaa65b1c8d782e7b776ae682679d2d948f">pcl::copyPointCloud</a></div><div class="ttdeci">PCL_EXPORTS void copyPointCloud(const pcl::PCLPointCloud2 &amp;cloud_in, const std::vector&lt; int &gt; &amp;indices, pcl::PCLPointCloud2 &amp;cloud_out)</div><div class="ttdoc">Extract the indices of a given point cloud as a new point cloud</div></div>
<div class="ttc" id="astruct_object_model_html"><div class="ttname"><a href="struct_object_model.html">ObjectModel</a></div><div class="ttdef"><b>Definition:</b> object_recognition.h:50</div></div>
<div class="ttc" id="astruct_object_recognition_parameters_html"><div class="ttname"><a href="struct_object_recognition_parameters.html">ObjectRecognitionParameters</a></div><div class="ttdef"><b>Definition:</b> object_recognition.h:16</div></div>
<div class="ttc" id="astructpcl_1_1_v_f_h_signature308_html"><div class="ttname"><a href="structpcl_1_1_v_f_h_signature308.html">pcl::VFHSignature308</a></div><div class="ttdoc">A point structure representing the Viewpoint Feature Histogram (VFH).</div><div class="ttdef"><b>Definition:</b> point_types.hpp:1366</div></div>
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